Dr. Laura B. Balzer is an Associate Professor of Biostatistics at the University of California, Berkeley. Her expertise is in causal inference, machine learning, and messy real-world data. Dr. Balzer's work addresses challenges in the design and analysis of both randomized trials and observational studies, including novel approaches for semi-parametric inference, differential measurement, and complex dependence. Dr. Balzer's work is largely been motivated by ongoing collaborations in Uganda and Kenya. She is the Primary Statistician for several studies aiming to eliminate HIV and...
Alejandro Schuler is an Assistant Professor in Residence at UC Berkeley Biostatistics. His research focus is on developing methods for clinical decision-making in the real world that are economically or clinically necessary, statistically rigorous, and frictionless from the user perspective. He completed his Ph.D. at Stanford in 2018 and worked as a postdoc with CTML before starting on the faculty. Dr. Schuler is known for developing the Selectively Adaptive Lasso, NGBoost, and prognostic covariate adjustment methods, among others. In addition, he often collaborates with domain...
